# A Tutorial on Hawkes Processes for Events in Social Media

arXiv: https://arxiv.org/abs/1708.06401 · HTML: https://mlsanity.com/paper/1708.06401/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Aug 2017.

## Built on by (most cited first, 15 of 15)

- [Bellman Meets Hawkes: Model-Based Reinforcement Learning via Temporal Point Processes](https://mlsanity.com/paper/2201.12569/) (2022)
- [TIGGER: Scalable Generative Modelling for Temporal Interaction Graphs](https://mlsanity.com/paper/2203.03564/) (2022)
- [Maximum Likelihood Estimation for Hawkes Processes with self-excitation or inhibition](https://mlsanity.com/paper/2103.05299/) (2021)
- [A Survey on Temporal Graph Representation Learning and Generative Modeling](https://mlsanity.com/paper/2208.12126/) (2022)
- [Bayesian Neural Hawkes Process for Event Uncertainty Prediction](https://mlsanity.com/paper/2112.14474/) (2021)
- [Online Detection Of Supply Chain Network Disruptions Using Sequential Change-Point Detection for Hawkes Processes](https://mlsanity.com/paper/2211.12091/) (2022)
- [Linking Across Data Granularity: Fitting Multivariate Hawkes Processes to Partially Interval-Censored Data](https://mlsanity.com/paper/2111.02062/) (2021)
- [Flexible Triggering Kernels for Hawkes Process Modeling](https://mlsanity.com/paper/2202.01869/) (2022)
- [HyperHawkes: Hypernetwork based Neural Temporal Point Process](https://mlsanity.com/paper/2210.00213/) (2022)
- [Survey on Modeling Intensity Function of Hawkes Process Using Neural Models](https://mlsanity.com/paper/2104.11092/) (2021)
- [Spatio-temporal extreme event modeling of terror insurgencies](https://mlsanity.com/paper/2110.08363/) (2021)
- [Le Processus Powered Dirichlet-Hawkes comme A Priori Flexible pour Clustering Temporel de Textes](https://mlsanity.com/paper/2201.12568/) (2022)
- [Interactions in Information Spread](https://mlsanity.com/paper/2209.08026/) (2022)
- [Stability of AI Governance Systems: A Coupled Dynamics Model of Public Trust and Social Disruptions](https://mlsanity.com/paper/2603.20248/) (2026)
- [HawkesLLM: Semantic Uncertainty Propagation in Agentic Text Simulation](https://mlsanity.com/paper/2605.23043/) (2026)

## Abstract (arXiv)

This chapter provides an accessible introduction for point processes, and especially Hawkes processes, for modeling discrete, inter-dependent events over continuous time. We start by reviewing the definitions and the key concepts in point processes. We then introduce the Hawkes process, its event intensity function, as well as schemes for event simulation and parameter estimation. We also describe a practical example drawn from social media data - we show how to model retweet cascades using a Hawkes self-exciting process. We presents a design of the memory kernel, and results on estimating parameters and predicting popularity. The code and sample event data are available as an online appendix